Table 1 Inputs and outputs of methods used for benchmarking
From: Protein remote homology detection and structural alignment using deep learning
Input data | Output alignment | |||
|---|---|---|---|---|
Tool | Sequence | Structure | Sequence | Structure |
Needleman–Wunsch | ✓ | ✓ | ||
Smith–Waterman | ✓ | ✓ | ||
BLAST | ✓ | ✓ | ||
HMMER | ✓ | ✓ | ||
Diamond | ✓ | ✓ | ||
HHBlits | ✓ | ✓ | ||
MMseq2 | ✓ | ✓ | ||
ProtTucker/EAT | ✓ | ✓ | ||
FoldSeek | ✓ | ✓ | ✓ | |
TM-align | ✓ | ✓ | ✓ | |
Dali | ✓ | ✓ | ✓ | |
FAST | ✓ | ✓ | ✓ | |
Mammoth | ✓ | ✓ | ✓ | |
TM-Vec + DeepBLAST | ✓ | ✓ | ✓ | |
